Image-registration method, medium, and apparatus

ABSTRACT

An image-registration method, medium, and apparatus obtaining first and second images, generating first and second image pyramids based on the first and second images, respectively, by performing sub-sampling which reduces the length and width of each of the first and second images by half, and determining one of five directions as an optimal movement direction for a current level of the first and second image pyramids based on two images belonging to a corresponding level, updating a motion vector for the current level based on the optimal movement direction for the current level and updating a first image belonging to a level directly below the current level based on the updated motion vector for the current level, wherein the updating comprises updating a motion vector for each of a plurality of levels of the first and second image pyramids in an order from an uppermost level to a lowermost level.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority from Korean Patent Application No.10-2007-0092231 filed on Sep. 11, 2007 in the Korean IntellectualProperty Office, the disclosure of which is incorporated herein byreference in its entirety.

BACKGROUND

1. Field

One or more embodiments relate to an image-registration method, medium,and apparatus, and, more particularly, to an image-registration method,medium, and apparatus in which image registration can be stablyperformed at high speed even on images having very different propertiesby using image pyramids and reducing the amount of computation requiredto calculate objective functions for each level of the image pyramids.

2. Description of the Related Art

Image registration is a process of geometrically matching two or moreimages that are physically similar to one another on a region-by-regionbasis.

In recent years, various image registration techniques have beensuggested that are capable of generating high dynamic range (HDR)images, performing image registration for the purpose of motiondeblurring or performing image registration on various types of images(e.g., an image captured by a typical camera and an image captured by aninfrared camera, or a computed tomography (CT) image and a magneticresonance imaging (MRI) image) captured by different image-capturingapparatuses with different modalities.

Conventional image-registration methods using a luminance-based methodcan be applied only to images obtained under similar photographingconditions (such as luminance or motion blur). Images obtained underdifferent photographing conditions are highly likely to have verydifferent properties from each other. If two images for which imageregistration is to be performed have very different properties from eachother, motion estimation for the two images may not be able to beproperly performed. For example, in the case of generating an HDR imageby performing image registration on two images obtained from differentexposure times, edge information of very bright or very dark regions inthe two images is highly likely to be lost especially when there is ahuge difference between the luminance levels of the two images. Inaddition, in the case of performing multiple exposure-based motiondeblurring on two images obtained from different exposure times, imageregistration may not be able to be properly performed because the amountof motion blur varies from one image to another due to the differentexposure times.

Conventional image-registration methods using a probability-based methodsuch as mutual information or normalized mutual information can enhancethe stability of image registration even when images have very differentproperties from each other, but are not suitable for use in camerasystems that operate online because of their considerable amounts ofcomputation.

SUMMARY

One or more embodiments provide an image-registration method, medium,and apparatus in which the speed of image registration can be improvedby using image pyramids and calculating only five objective functionsfor each level of the image pyramids, and in which image registrationcan be stably performed even on images having very different propertiesfrom each other by calculating objective functions using a conventionalprobability-based method.

Additional aspects and/or advantages will be set forth in part in thedescription which follows and, in part, will be apparent from thedescription, or may be learned by practice of the invention.

According to an aspect of the present invention, there is provided animage-registration method including obtaining a first image and a secondimage, generating first and second image pyramids based on the first andsecond images, respectively, by performing sub-sampling which reducesthe length and width of each of the first and second images by half, anddetermining one of five directions respectively corresponding to (−1,0), (1, 0), (0, 0), (0, −1), and (0, 1) as an optimal movement directionfor a current level of the first and second image pyramids based on twoimages belonging to a corresponding level, updating a motion vector forthe current level based on the optimal movement direction for thecurrent level and updating a first image belonging to a level directlybelow the current level based on the updated motion vector for thecurrent level, wherein the updating comprises updating a motion vectorfor each of a plurality of levels of the first and second image pyramidsin an order from an uppermost level to a lowermost level.

According to another aspect of the present invention, there is providedan image-registration apparatus including an image-capturing modulewhich obtains a first image and a second image using an image sensor, apyramid-generation module which generates first and second imagepyramids based on the first and second images, respectively, byperforming sub-sampling which reduces the length and width of each ofthe first and second images by half, a direction-calculation modulewhich determines one of five directions respectively corresponding to(−1, 0), (1, 0), (0, 0), (0, −1), and (0, 1) as an optimal movementdirection for a current level of the first and second image pyramidsbased on two images belonging to the current level, amotion-vector-calculation module which updates a motion vector for thecurrent level based on the optimal movement direction for the currentlevel, and an image-update module which updates a first image belongingto a level directly below the current level based on the updated motionvector for the current level, wherein the motion-vector-calculationmodule calculates a motion vector for each of a plurality of levels ofthe first and second image pyramids in an order from an uppermost levelto a lowermost level.

BRIEF DESCRIPTION OF THE DRAWINGS

These and/or other aspects and advantages will become apparent and morereadily appreciated from the following description of the embodiments,taken in conjunction with the accompanying drawings of which:

FIG. 1 illustrates a flowchart of an image-registration method accordingto an embodiment of the present invention;

FIG. 2 illustrates an image pyramid obtained by sub-sampling whichreduces the length and width of an image by half, according to anembodiment of the present invention;

FIG. 3 illustrates an actual image pyramid obtained by sub-samplingwhich reduces the length and width of an image by half;

FIG. 4 illustrates five directions used to estimate an optimal movementdirection, according to an embodiment of the present invention;

FIG. 5 illustrates two image pyramids and optimal movement directionsdetermined for respective corresponding levels of the two imagepyramids;

FIG. 6 illustrates a final motion vector updated based on optimalmovement directions determined for respective corresponding levels ofimage pyramids, according to an embodiment of the present invention; and

FIG. 7 illustrates a block diagram of an image-registration apparatusaccording to an embodiment of the present invention.

DETAILED DESCRIPTION OF EMBODIMENTS

Reference will now be made in detail to embodiments, examples of whichare illustrated in the accompanying drawings, wherein like referencenumerals refer to like elements throughout. In this regard, embodimentsof the present invention may be embodied in many different forms andshould not be construed as being limited to embodiments set forthherein. Accordingly, embodiments are merely described below, byreferring to the figures, to explain aspects of the present invention.

FIG. 1 illustrates a flowchart of an image-registration method accordingto an embodiment of the present invention. Referring to FIG. 1, theimage-registration method includes obtaining a first image and a secondimage with the aid of an image-capturing apparatus (S110 a and S110 b),converting the first and second images into mono-channel images (S120 aand S120 b), generating two image pyramids, i.e., first and second imagepyramids using sub-sampling (S130 a and S130 b), determining optimalmovement directions for each of a plurality of levels of the first andsecond image pyramids based on two images belonging to a correspondinglevel of the first and second image pyramids (S150 and S200), updating amotion vector based on an optimal movement direction (S160), determiningwhether the current level is the lowermost level of the image pyramids(S170), and updating a first image belonging to a level directly below alevel currently being set based on the updated motion vector (S190 andS210).

Specifically, referring to FIGS. 1 and 7, two images, i.e., first andsecond images, are obtained using an image-capturing module 510, whichincludes an image sensor (S110 a and S110 b).

Image sensors are elements of image-capturing apparatuses which generatean image by converting light reflected from a subject into an electricimage signal, and are largely classified into charge-coupled device(CCD) image sensors and complementary metal oxide semiconductor (CMOS)image sensors according to how they are manufactured and how theyoperate.

According to an embodiment of the present invention, it is possible tostably perform image registration not only on images obtained using oneimage-capturing apparatus but also on images obtained by using more thanone image-capturing apparatus with different modalities. For example,according to an embodiment of the present invention, it is possible toperform image registration on an image obtained by a typical camera andan image obtained by an infrared (IR) camera or on a computed tomography(CT) image and a magnetic resonance imaging (MRI) image. Thus,embodiments of the present invention can be widely applied to variousimaging systems. Therefore, according to embodiments of the presentinvention, it is possible to perform image registration regardless ofthe type(s) of image-capturing apparatus(es) and the number ofimage-capturing apparatuses used to obtain the first and second images.

Thereafter, an image-conversion module 520 converts the first and secondimages into mono-channel images (S120 a and S120 b). Examples of themono-channel images include grayscale images and images with only one ofred (R), green (G) and blue (B) channels.

Since the first and second images are converted into mono-channelimages, it is possible to perform image registration on various types ofimages, for example, color images, black-and-white images, IR images, ormedical images such as CT or MRI images.

Thereafter, a pyramid-generation module 530 generates two imagepyramids, i.e., first and second image pyramids, using the first andsecond images or using the mono-channel images generated by theimage-conversion module 520.

FIG. 2 illustrates an image pyramid obtained by sub-sampling thatreduces the length and width of an image by half, according to anembodiment of the present invention, and FIG. 3 illustrates an actualimage pyramid obtained by sub-sampling that reduces the length and widthof an image by half.

In general, during image registration, a considerable amount of dataneeds to be processed in order to extract a motion vector from a sourceimage, and, thus, the time required to perform image-registrationincreases. In order to address this, image pyramids may be used toreduce the size of images to be processed while keeping the propertiesof the images intact.

Referring to FIGS. 2 and 3, when an image having the same size as anoriginal image is referred to as a zeroth-level image, an image havingthe smallest size is referred to as an n-th-level image (where n=5), andthe smaller the size of an image, the higher the level of the image. Inthis case, the higher the level of an image, the lower the resolution ofthe image, and the lower the level of an image, the higher theresolution of the image.

In the embodiment of FIGS. 2 and 3, an image pyramid is generated byperforming sub-sampling, which reduces the length and width of an imageby half, for each level. Thus, whenever such sub-sampling is performed,the number of pixels of an image is reduced by one fourth, and the sizeof the image is also reduced by one fourth. Sub-sampling may beperformed by dividing an image into a number of 2×2 regions, extractinga pixel at a predetermined location in each of the 2×2 regions andgenerating a new image based on the extracted pixels. Since an imagebelonging to a level directly above the level of the original image isgenerated by selecting one pixel from the 2×2 regions, the size of theimage belonging to the level directly above the level of the originalimage is one fourth of the size of the original image, and theresolution of the image belonging to the level directly above the levelof the original image is lower than the resolution of the originalimage.

Referring to FIG. 1, image registration is performed on the first andsecond images by updating a motion vector of each of a plurality oflevels of the first and second image pyramids in the order from anuppermost level to a lowermost level of the first and second imagepyramids.

Specifically, the uppermost level of the first and second image pyramidsof the first and second images, i.e., an n-th level, is set as a currentlevel (S140). Then, a direction-calculation module 540 determines one offive directions respectively corresponding to (−1, 0), (1, 0), (0, 0),(0, −1), and (0, 1) as an optimal movement direction based on two imagesbelonging to the uppermost level of the first and second image pyramids(S150).

FIG. 4 illustrates five directions used to determine an optimal movementdirection, according to an embodiment of the present invention.Referring to FIG. 4, five objective functions for determining a motionvector are set for the respective five directions, and it is determinedwhich of the objective functions produces a maximum value. Then, adirection corresponding to whichever of the objective functions producesa maximum value is determined as an optimal movement direction.Therefore, an optimal movement direction v_(n) for the uppermost levelof the first and second image pyramids, i.e., the n-th level,corresponds to one of (−1, 0), (1, 0), (0, 0), (0, −1), and (0, 1).

In order to determine an optimal movement direction, a conventionalluminance-based or probability-based method may be used. Theluminance-based method may use a correlation algorithm, a normalizedcorrelation algorithm or a sum of the absolute difference (SAD)algorithm, and the probability-based method may use a mutual informationalgorithm or a normalized mutual information algorithm. Since thecorrelation, normalized correlation, SAD, mutual information andnormalized mutual information algorithms are well known to one ofordinary skill in the art to which embodiments of the present inventionpertain, detailed descriptions thereof will be skipped.

By using the probability-based method, it is possible to stably performimage registration even on images having very different properties.However, the probability-based method results in a considerable amountof computation. In contrast, according to embodiments of the presentinvention, it is possible to reduce the required amount of computation,and thus to perform image registration at high speed by calculating onlyfive objective functions for each level of image pyramids using theprobability-based method.

Referring again to FIG. 1, once the optimal movement direction v_(n) forthe n-th level is determined, the motion-vector-calculation module 550calculates a motion vector for the n-th level based on the optimalmovement direction v_(n) (S160).

Thereafter, a level directly below the n-th level, i.e., an (n−1)-thlevel, is set as a new current level (S180). Then, an image-updatemodule 560 updates a first image belonging to the (n−1)-th level basedon the motion vector for the n-th level (S190). A motion vector forupdating the first image belonging to the (n−1)-th level is 2v_(n)because the length and width of an image belonging to a particular levelof an image pyramid are respectively twice the length and width of animage belonging to a level directly above the particular level, and thusa motion vector for the particular level of an image pyramid is twice amotion vector for the level directly above the particular level.

Thereafter, the direction-calculation module 540 determines an optimalmovement direction v_(n−1) based on the updated first image belonging tothe (n−1)-th level and a second image belonging to the (n−1)-th level(S200). Operation S200 is performed in the same manner as operationS150. The optimal movement direction v_(n−1), like the optimal movementdirection v_(n), corresponds to one of (−1, 0), (1, 0), (0, 0), (0, −1),and (0, 1).

Thereafter, the motion-vector-calculation module 550 updates the motionvector for updating the first image belonging to the (n−1)-th levelbased on the optimal movement direction v_(n−1) by doubling the optimalmovement direction v_(n) and adding the optimal movement directionv_(n−1) to the result of the doubling (S160). As a result, the motionvector for updating the first image belonging to the (n−1)-th level isupdated with 2v_(n)+v_(n−1). Thereafter, a level directly below the(n−1)-th level, i.e., an (n−2)-th level, is set as a new current level(S180). Then, the image-update module 560 updates a first imagebelonging to the (n−2)-th level based on the updated motion vector2v_(n)+v_(n−1) obtained in operation S160 (S190). A motion vector forupdating the first image belonging to the (n−2)-th level is2²v_(n)+2v_(n−1), which is twice the motion vector determined for the(n−1)-th level. The optimal movement direction v_(n) for the n-th levelcontributes to motions in an image belonging to the (n−2)-th level by 2²times as much as it does to motions in an image belonging to the n-thlevel because the length and width of the image belonging to the n-thlevel are respectively 2² times less than the length and width of theimage belonging to the (n−2)-th level. Likewise, the optimal movementdirection v_(n−1) for the (n−1)-th level contributes to the update of animage belonging to the (n−2)-th level by two times as much as it does tothe update of an image belonging to the (n−1)-th level because thelength and width of the image belonging to the (n−1)-th level arerespectively half the length and width of the image belonging to the(n−2)-th level. Therefore, a motion vector for updating a first imagebelonging to the (n−2)-th level is determined to be 2²v_(n)+2v_(n−1).

Thereafter, the direction-calculation module 540 determines an optimalmovement direction based on the updated first image belonging to the(n−2)-th level and a second image belonging to the (n−2)-th level(S200), and updates the motion vector (S160). Operations S160 throughS200 are performed repeatedly until the lowermost level of the first andsecond image pyramids, i.e., a zeroth level, is set as a new currentlevel.

In this manner, an updated motion vector for a first level obtained inoperation S160 is determined to be 2^(n−1)v_(n)+2^(n−1)v_(n)+ . . . +v₁,and a motion vector for updating a first image belonging to the zerothlevel is determined to be 2^(n)v_(n)+2^(n)v_(n)+ . . . +2v₁, which istwice the updated motion vector for the first level. Then, an optimalmovement direction v₀ for the zeroth level is determined based on anupdated first image belonging to the zeroth level and a second imagebelonging to the zeroth level, and the motion vector for updating thefirst image belonging to the zeroth level is updated with2^(n)v_(n)+2^(n−1)v_(n)+ . . . +2v₁+v₀. In this case, since the currentlevel is the uppermost level of the first and second image pyramids,i.e., the first image belong to the zeroth level is updated based on themotion vector 2^(n)v_(n)+2^(n−1)v_(n)+ . . . +2v₁+v₀ (S210).

In this manner, the motion vector for updating the lowermost level ofthe first and second image pyramids may be determined to be2^(n)v_(n)+2^(n−1)v_(n)+ . . . +2v₁+v₀, and the original first image maybe updated based on the motion vector 2^(n)v_(n)+2^(n−1)v_(n)+ . . .+2v₁+v₀, thereby completing image registration.

FIG. 5 illustrates optimal movement directions (or motion vectors)determined for respective corresponding levels of first and second imagepyramids, and FIG. 6 illustrates a final motion vector updated based onthe optimal movement directions determined for the respective levels ofthe first and second image pyramids illustrated in FIG. 5.

Referring to FIG. 5, for an uppermost level of the first and secondimage pyramids, i.e., an n-th level, an optimal movement direction isdetermined based on a first image and a second image belonging to then-th level, whereas, for each of the (n−1)-th through zeroth levels ofthe first and second image pyramids, a first image belonging to acorresponding level is updated based on a motion vector determined for alevel directly above the corresponding level, and an optimal movementdirection is determined based on the updated first image and a secondimage belonging to the corresponding level. A final motion vectorobtained using optimal movement directions v_(n), v_(n−1), . . . , v₁and v₀ respectively determined for the n-th through zeroth levels of thefirst and second image pyramids, respectively, is illustrated in FIG. 6.Since each of the optimal movement directions v_(n), v_(n−1), . . . , v₁and v₀ corresponds to one of (1, 0), (−1, 0), (0, 0), (0, 1), and (0,−1), the vector length of an optimal movement direction may graduallydecrease for lower levels of the first and second image pyramids

FIG. 7 illustrates a block diagram of an image-registration apparatusaccording to an embodiment of the present invention. Herein, the termapparatus should be considered synonymous with the term system, and notlimited to a single enclosure or all described elements embodied insingle respective enclosures in all embodiments, but rather, dependingon embodiment, is open to being embodied together or separately indiffering enclosures and/or locations through differing elements, e.g.,a respective apparatus/system could be a single processing element orimplemented through a distributed network, noting that additional andalternative embodiments are equally available.

Referring to FIG. 7, the image-registration apparatus includes theimage-capturing module 510, the pyramid-generation module 530, thedirection-calculation module 540, the motion-vector-calculation module550, and the image-update module 560. The image-registration apparatusmay also include the image-conversion module 520.

Referring to FIG. 7, the image-capturing module 510 may include an imagesensor which detects light reflected from a subject, and converts thelight into an electric signal. The image-capturing module 510 obtainstwo images, i.e., first and second images.

The pyramid-generation module 530 generates first and second imagepyramids by performing sub-sampling, which reduces the length and widthof each of the first and second images by half.

The direction-calculation module 540 determines one of five directionsrespectively corresponding to (−1, 0), (1, 0), (0, 0), (0, −1), and(0, 1) as an optimal movement direction for a current level of the firstand second image pyramids based on two images belonging to the currentlevel using a luminance-based method or a probability-based method. Theluminance-based method may use the correlation algorithm, normalizedcorrelation algorithm or sum of the absolute difference (SAD) algorithm,and the probability-based method may use the mutual informationalgorithm or the normalized mutual information algorithm.

The motion-vector-calculation module 550 updates a motion vector basedon the optimal movement direction determined for the current level. Theupdate of a motion vector has already been described above, and thus, adetailed description thereof will be skipped.

The image-update module 560 updates a first image belonging to a leveldirectly below the current level based on the updated motion vectorobtained by the motion-vector-calculation module 550.

The update of a motion vector and the update of a first image areperformed for each of a plurality of levels of the first and secondimage pyramids in the order from an uppermost level to a lowermost levelof the first and second image pyramids. Once a motion vector for aparticular level of the first and second image pyramids is updated, afirst image belonging to a level directly below the particular level isupdated, and a motion vector for the level directly below the particularlevel is updated based on the updated first image and a second imagebelonging to the level directly below the particular level. In thismanner, a final motion vector for image registration is obtained.

The image-conversion module 520 may perform grayscale conversion on thefirst and second images obtained by the image-capturing module 510.

Briefly, the term “module”, as used herein, means, but is not limitedto, a software or hardware component, such as a Field Programmable GateArray (FPGA) or Application Specific Integrated Circuit (ASIC), whichperforms certain tasks. A module may advantageously be configured toreside on the addressable storage medium and configured to execute onone or more processors. Thus, a module may include, by way of example,components, such as software components, object-oriented softwarecomponents, class components and task components, processes, functions,attributes, procedures, subroutines, segments of program code, drivers,firmware, microcode, circuitry, data, databases, data structures,tables, arrays, and variables. The capability provided for in thecomponents and modules may be combined into fewer components and modulesor further separated into additional components and modules.

In addition, embodiments of the present invention have been describedabove with reference to flowchart illustrations of user interfaces,methods, and media according to embodiments of the invention. It will beunderstood that each block of the flowchart illustrations, andcombinations of blocks in the flowchart illustrations, can beimplemented by computer readable code, as noted below. These computerreadable code instructions can be provided to a processor of a generalpurpose computer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create mechanisms for implementing thefunctions specified in the flowchart block or blocks, for example.

Further, each block of the flowchart illustrations may represent amodule, segment, or portion of code, which includes one or moreexecutable instructions, i.e., computer readable code, for implementingthe specified logical function(s). It should also be noted that in somealternative implementations, the functions noted in the blocks may occurout of the order. For example, two blocks shown in succession may infact be executed substantially concurrently or the blocks may sometimesbe executed in the reverse order, depending upon the functionalityinvolved.

Accordingly, in view of the above, and in addition to the abovedescribed embodiments, embodiments of the present invention can also beimplemented through computer readable code/instructions in/on a medium,e.g., a computer readable medium, to control at least one processingelement to implement any above described embodiment. The medium cancorrespond to any medium/media permitting the storing and/ortransmission of the computer readable code.

The computer readable code can be recorded/transferred on a medium in avariety of ways, with examples of the medium including recording media,such as magnetic storage media (e.g., ROM, floppy disks, hard disks,etc.) and optical recording media (e.g., CD-ROMs, or DVDs), andtransmission media such as media carrying or including carrier waves, aswell as elements of the Internet, for example. Thus, the medium may besuch a defined and measurable structure including or carrying a signalor information, such as a device carrying a bitstream, for example,according to embodiments of the present invention. The media may also bea distributed network, so that the computer readable code isstored/transferred and executed in a distributed fashion. Still further,as only an example, the processing element could include a processor ora computer processor, and processing elements may be distributed and/orincluded in a single device.

As described above, the image-registration method, medium, and apparatusaccording to embodiments of the present invention have the followingadvantages.

First, it is possible to improve the speed of image registration byusing image pyramids and calculating only five objective functions foreach level of the image pyramids.

Second, it is possible to apply embodiments of the present invention tocamera systems that operate online and thus to easily realize hardwaredevices by reducing the amount of computation required for imageregistration.

Third, it is possible to stably perform image registration on imageshaving very different properties (such as different luminances, motionblur levels, and modalities) from each other by using aprobability-based method such as the mutual information algorithm andthe normalized mutual information algorithm to calculate five objectivefunctions for each level of image pyramids.

While aspects of the present invention has been particularly shown anddescribed with reference to differing embodiments thereof, it should beunderstood that these exemplary embodiments should be considered in adescriptive sense only and not for purposes of limitation. Descriptionsof features or aspects within each embodiment should typically beconsidered as available for other similar features or aspects in theremaining embodiments.

Thus, although a few embodiments have been shown and described, it wouldbe appreciated by those skilled in the art that changes may be made inthese embodiments without departing from the principles and spirit ofthe invention, the scope of which is defined in the claims and theirequivalents.

1. An image-registration method comprising: obtaining a first image anda second image; generating first and second image pyramids based on thefirst and second images, respectively, by performing sub-sampling whichreduces the length and width of each of the first and second images byhalf; and determining one of five directions respectively correspondingto (−1, 0), (1, 0), (0, 0), (0, −1), and (0, 1) as an optimal movementdirection for a current level of the first and second image pyramidsbased on two images belonging to a corresponding level, updating amotion vector for the current level based on the optimal movementdirection for the current level and updating a first image belonging toa level directly below the current level based on the updated motionvector for the current level, wherein the updating of the motion vectorcomprises updating a motion vector for each of a plurality of levels ofthe first and second image pyramids in an order from an uppermost levelto a lowermost level.
 2. The image-registration method of claim 1,further comprising converting the first and second images intomono-channel images.
 3. The image-registration method of claim 2,wherein the mono-channel images are grayscale images.
 4. Theimage-registration method of claim 1, wherein the determining comprisesdetermining the optimal movement direction for the current level usingone of a luminance-based method and a probability-based method.
 5. Theimage-registration method of claim 4, wherein the luminance-based methoduses one of a correlation algorithm, a normalized correlation algorithm,and a sum of absolute differences (SAD) algorithm.
 6. Theimage-registration method of claim 4, wherein the probability-basedmethod uses one of a mutual information algorithm and a normalizedmutual information algorithm.
 7. The image-registration method of claim1, wherein, if there are n+1 image pyramids and a plurality of levels ofthe n+1 pyramids ranging from a lowermost level to an uppermost levelare respectively referred to as zeroth, first, . . . , n-th levels, amotion vector V may be defined by the equation:${V = {\sum\limits_{k = 0}^{n}\; {2^{n - k}v_{n - k}}}},$ where v_(k)indicates an optimal movement direction determined for a k-th level. 8.An image-registration apparatus comprising: an image-capturing modulewhich obtains a first image and a second image using an image sensor; apyramid-generation module which generates first and second imagepyramids based on the first and second images, respectively, byperforming sub-sampling which reduces the length and width of each ofthe first and second images by half; a direction-calculation modulewhich determines one of five directions respectively corresponding to(−1, 0), (1, 0), (0, 0), (0, −1), and (0, 1) as an optimal movementdirection for a current level of the first and second image pyramidsbased on two images belonging to the current level; amotion-vector-calculation module which updates a motion vector for thecurrent level based on the optimal movement direction for the currentlevel; and an image-update module which updates a first image belongingto a level directly below the current level based on the updated motionvector for the current level, wherein the motion-vector-calculationmodule calculates a motion vector for each of a plurality of levels ofthe first and second image pyramids in an order from an uppermost levelto a lowermost level.
 9. The image-registration apparatus of claim 8,further comprising an image-conversion module which converts the firstand second images into mono-channel images.
 10. The image-registrationapparatus of claim 9, wherein the mono-channel images are grayscaleimages.
 11. The image-registration apparatus of claim 8, wherein thedirection-calculation module determines the optimal movement directionfor the current level using one of a luminance-based method and aprobability-based method.
 12. The image-registration apparatus of claim11, wherein the luminance-based method uses one of a correlationalgorithm, a normalized correlation algorithm, and a sum of absolutedifferences (SAD) algorithm.
 13. The image-registration apparatus ofclaim 11, wherein the probability-based method uses one of a mutualinformation algorithm and a normalized mutual information algorithm. 14.The image-registration apparatus of claim 8, wherein, if there are n+1image pyramids and a plurality of levels of the n+1 pyramids rangingfrom a lowermost level to an uppermost level are respectively referredto as zeroth, first, . . . , n-th levels, a motion vector V may bedefined by the equation:${V = {\sum\limits_{k = 0}^{n}\; {2^{n - k}v_{n - k}}}},$ where v_(k)indicates an optimal movement direction determined for a k-th level.